Representing a machine-to-machine device model based on ontological relationships

ABSTRACT

In an approach for creating a machine-to-machine device model based on ontological relationship, one or more computer processors determine a plurality of characteristics of one or more machine-to-machine devices within a machine-to-machine communication environment. The one or more computer processors determine one or more ontological relationships between the one or more machine-to-machine devices and the plurality of characteristics of the one or more machine-to-machine devices. The one or more computer processors create a semantic device model, based, at least in part, on the one or more ontological relationships between the one or more machine-to-machine devices and the plurality of characteristics of the one or more machine-to-machine devices.

FIELD OF THE INVENTION

The present invention relates generally to the field of computer networkmanagement, and more particularly to creating and representing amachine-to-machine device model based on ontological relationships.

BACKGROUND OF THE INVENTION

Machine-to-machine (“M2M”) technology includes a form of datacommunication that involves one or more entities, or devices, that donot necessarily require human interaction or intervention in the processof communication. The M2M communication may enable different types ofservices that are valuable to an end user. For example, M2Mcommunication services may include smart metering, healthcare monitoring(e.g., patient monitoring), remote security sensing, smart grid, weathermonitoring, etc. M2M architecture may include a variety of elements suchas M2M devices (e.g., a sensor, an actuator), M2M area network, M2Mcommunication network, and/or an M2M application service server.Typically, M2M applications may be configured or developed based on M2Mplatforms, which may be used to provide a variety of M2M applicationservices based on the collected device data.

SUMMARY

Embodiments of the present invention are directed to a method, computerprogram product, and computer system for creating a machine-to-machinedevice model based on ontological relationship. The method includes oneor more computer processors determining a plurality of characteristicsof one or more machine-to-machine devices within a machine-to-machinecommunication environment. The one or more computer processors determineone or more ontological relationships between the one or moremachine-to-machine devices and the plurality of characteristics of theone or more machine-to-machine devices. The one or more computerprocessors create a semantic device model, based, at least in part, onthe one or more ontological relationships between the one or moremachine-to-machine devices and the plurality of characteristics of theone or more machine-to-machine devices.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a distributed M2Mcommunication environment, in accordance with an embodiment of thepresent invention.

FIG. 2 is a flowchart depicting operational steps of a modeling program,for determining and representing ontological relationships betweendevice characteristics in the distributed M2M communication environmentof FIG. 1, in accordance with an embodiment of the present invention.

FIG. 3 is a flowchart depicting operational steps of a performanceprogram, for determining a device given conditions and parameters ofuse, using the model created by the modeling program of FIG. 2, inaccordance with an embodiment of the present invention.

FIG. 4 depicts a block diagram of components of a server computer, suchas the server computer of FIG. 1 executing the modeling program and theperformance program, in accordance with an embodiment of the presentinvention.

DETAILED DESCRIPTION

The present invention will now be described in detail with reference tothe Figures. FIG. 1 is a functional block diagram illustrating adistributed M2M communication environment, generally designated 100, inaccordance with one embodiment of the present invention. FIG. 1 providesonly an illustration of one implementation and does not imply anylimitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironment may be made by those skilled in the art without departingfrom the scope of the invention as recited by the claims.

Distributed M2M communication environment 100 includes server computer120, client computing device 130, and devices 140A to 140N, allinterconnected over network 110. Network 110 may be a local area network(LAN), a wide area network (WAN), such as the Internet, any combinationof the two, or any combination of connections and protocols that willsupport communication between server computer 120, client computingdevice 130, and devices 140A to 140N, in accordance with embodiments ofthe present invention. Network 110 may include wired, wireless, or fiberoptic connections.

Server computer 120 may be a laptop computer, a tablet computer, anetbook computer, a personal computer (PC), a personal digital assistant(PDA), a smart phone, or any programmable electronic device capable ofcommunicating with client computing device 130 and devices 140A to 140N.Server computer 120 may be a management server, a web server, or mayrepresent a computing system utilizing clustered computers andcomponents to act as a single pool of seamless resources when accessedthrough a network. Server computer 120 may include internal and externalcomponents, as depicted and described in further detail with respect toFIG. 4.

Server computer 120 includes data management platform 122, modelingprogram 124, performance program 126, and device database 128. Datamanagement platform 122 is a computing platform, or computing system,capable of receiving, integrating, and managing data and informationfrom a variety of sources, for example, devices 140A to 140N. Datamanagement platform 122 processes incoming device data, includingadministration and management functions, and communicates theinformation to modeling program 124 and performance program 126, and toclient computing device 130 via network 110.

Modeling program 124 determines device characteristics of devices withindistributed M2M communication environment 100, such as devices 140A to140N, and creates semantic models for the devices 140A to 140Nrepresenting ontological relationships between device characteristicsand various components and elements, or generally, how devicecharacteristics, components, and elements are related to each otherwithin distributed M2M communication environment 100. For example,modeling program 124 can determine ontological relationships betweenvarious device characteristics and metrological entities, hardwarecomponents, software components, business attributes, device attributes,protocols (including transport level protocols), performance parameters,connectivity mediums, or any other component, characteristic, or elementof a device. Metrological entities in a M2M environment ensure thatregardless of how a physical quantity is measured, received, orrepresented, it is interpreted correctly. Metrological entities include,for example, standards used in the M2M industry and any relationshipsbetween various standards, systems of measure, units of measure, andphysical quantity information such as base units (fundamental units),derived units, or hybrid units, such as blood sugar or blood pressurequantities which are more commonly referred to using unique units.Business attributes can be, for example, measureable attributes forwhich the device exists, including what the device is meant to measure,what boundary conditions are for the device's measurements, and whatunit of measurement the device uses. Device attributes can be, forexample, attributes that describe quantifiable parameters needed todescribe the device itself, including descriptive attributes providingmetadata about how a device is different from other existing devicetypes.

Modeling program 124 represents the ontological relationships and devicecharacteristics in a semantic device model, which can aid in determiningcapabilities of a device and protocols supported by a device. A semanticdevice model describes relationships between various data elements, forexample, device characteristics, and real world information, andinterrelationships of the data elements with other data elements. Therelationships can be, generally, a description of the relationship amongcomponents within distributed M2M communication environment 100 and eachof devices 140A to 140N. For example, ontological relationships amongand between metrological entities ensure that a term or measurement isproperly interpreted, for example, the physical quantity “pressure”could be stored in pounds per square inch (psi), Pascals, or dynes persquare centimeters, and an ontological relationship represented in asemantic device model can aid in interpreting the received pressuremeasurement. While shown in FIG. 1 as individual programs, one of skillin the art will recognize that modeling program 124 and performanceprogram 126 can be implemented as one program. Additionally, whilemodeling program 124 and performance program 126 are shown in FIG. 1 onserver computer 120, one of skill in the art will recognize each programcan function elsewhere in distributed M2M communication environment 100with access to device 140A to 140N and device database 128 via network110.

Performance program 126 determines, using the device model created bymodeling program 124, configurations of devices and performanceparameters that can be set within distributed M2M communicationenvironment 100 for various business applications, such as businessapplication 132. Device database 128 contains device types, individualdevice component information, created device models, and ontologicalrelationship information among device components.

Client computing device 130 may be a laptop computer, a tablet computer,a netbook computer, a PC, a PDA, a smart phone, or any programmableelectronic device capable of communicating with server computer 120 anddevices 140A to 140N via network 110. Client computing device 130includes business application 132. Business application 132 can be acomputer software application, system software, programming tool, or anyapplication running on client computing device 130 that can translateinformation gathered from devices 140A to 140N into meaningfulinformation for use with a business process. Business application 132can be, for example, a safety program, a maintenance program, a salesprogram, a facility management program, or any other softwareapplication or program that uses the information obtained and gatheredfrom devices 140A to 140N.

Devices 140A to 140N can be electronic devices, for example, a sensor,including a heat sensor, a humidity sensor, or a light sensor, anactuator, a radio-frequency identification (“RFID”) tag reader, acamera, or a meter, which captures an event, such as a temperaturereading or inventory information. Devices 140A to 140N can communicatedata through a network, either wired or wireless, for example, network110.

FIG. 2 is a flowchart depicting operational steps of modeling program124, for determining and representing ontological relationships betweendevice characteristics in distributed M2M communication environment 100,in accordance with an embodiment of the present invention.

Modeling program 124 determines device characteristics (step 202).Device characteristics include, for example, protocol supports,performance parameters, hardware components, software components,connectivity mediums, metrological entities, and other capabilities andcharacteristics of the device, for example, each of device 140A to 140Nin distributed M2M communication environment 100.

Modeling program 124 determines whether the device exists in devicedatabase 128 (decision block 204). Modeling program 124 checks for adevice having the determined device characteristics, and if the devicetype already exists in device database 128 (decision block 204, “yes”branch), no further processing occurs. If the device does not exist indevice database 128 (decision block 204, “no” branch), modeling program124 parses individual components of the device (step 206). In anembodiment of the present invention, modeling program 124 can also checka standards organization for ontological relationship information forcharacteristics of the device, for example, when determiningmetrological entity relationships or protocol relationships.

Modeling program 124 parses individual components of the device, forexample, hardware and software components, protocols, metrologicalentities, performance parameters, connectivity mediums, and device typeclassification information. Modeling program 124 determines if theindividual parsed components of the device exist in device database 128(decision block 208). If the individual parsed components do exist indevice database 128 (decision block 208, “yes” branch), modeling program124 creates a device model for the device type using the storedrelationship information in device database 128. If the individualparsed components do not exist in device database 128 (decision block208, “no” branch), modeling program 124 determines ontologicalrelationships between the individual components of the device (step210). In an embodiment of the present invention, modeling program 124determines ontological relationships and component characteristics foreach component individually, for example, relationships involvinghardware components, and then relationships involving protocols.

Modeling program 124 generates and creates a semantic device model forthe device type using the ontological relationships between theindividual parsed components (step 212). The created device modelrepresents ontological relationships between the individual componentsof the device. In an embodiment, the semantic device model uses WebOntology Language (OWL) or Resource Description Framework (RDF) as ageneral method of conceptual description and modeling. The createddevice model represents capabilities of the device, for example,communication protocols supported and configurations of the device thatcan be read or set. The created device model can aid in configurationand backup of devices and can allow for intelligent queries against thedevice model. Queries against a device model may include, for example,whether a device type is capable of supporting high-level communicationprotocols used to create personal area networks built from small,low-power digital radios, or whether a ‘device A’, belonging generallyto ‘device type a’, can be used in place of ‘device B’, belonginggenerally to ‘device type b’.

Additionally, maintaining ontological relationships between a device andvarious device characteristics can remove ambiguity arising from devicereadings. For example, if there are three thermal sensors in distributedM2M communication environment 100, each reporting measurements indifferent units, data received from each device may be difficult tointerpret. However, if an ontological relationship between a thermalsensor measuring liquid nitrogen in Kelvin and the metrological entityreceiving the quantity measurement is known, the data returned from thethermal sensor may be properly interpreted.

Modeling program 124 determines whether the created model is approved(decision block 214). In an embodiment, the created device model is sentto a device modeler or administrator for approval. In variousembodiments, the device modeler or administrator can add rules andrelationships for certain device characteristics, for example,relationships for and between hardware components and softwarecomponents. If the created device model is not approved (decision block214, “no” branch), the device model is rejected and removed. If thecreated model is approved (decision block 214, “yes” branch), modelingprogram 124 updates device database 128 with the created model andstores the ontological relationship information (step 216).

FIG. 3 is a flowchart depicting operational steps of a performanceprogram, for determining a device given conditions and parameters ofuse, using the model created by the modeling program of FIG. 2, inaccordance with an embodiment of the present invention.

Performance program 126 determines current performance parameters (step302). For optimum performance in connection with business application132, performance program 126 determines, for example, bandwidth needed,storage required, data accessibility, and other performance parametersof the device represented by the created device model. In an embodiment,optimum performance parameters for current conditions may be determinedby accessing device vendors and standards databases. In variousembodiments of the present invention, performance program 126 can rankthe determined performance parameters in order of most important for thedevice to operate to least important for the device, or vice versa.

Performance program 126 determines current connectivity mediums (step304). Based on given parameters and current conditions such as businessapplication 132, device location, cost of network, user reviews, andservice provider performance, performance program 126 determines whichdevice model is best for available connection mediums. In an embodiment,performance program 126 can create a model for connectivity mediumswhich shows the relationship between the device model and theconnectivity mediums, for example, WiFi, wired, 3G, LTE, and others, andprovides information on which is best for the device to connect to atwhat time and what location.

Performance program 126 determines a device for the current performanceparameters and current connectivity mediums using the created devicemodel and the current condition information (step 306). The currentparameters and condition information may be, for example, retrieved frombusiness application 132 or inputted by a user within distributed M2Mcommunication environment 100. Based on the current parameters andcondition information, a “best” device, or a device suited for optimumperformance, as compared with other available devices, may bedetermined.

FIG. 4 depicts a block diagram of components of server computer 120 inaccordance with an illustrative embodiment of the present invention. Itshould be appreciated that FIG. 4 provides only an illustration of oneimplementation and does not imply any limitations with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environment may be made.

Server computer 120 includes communications fabric 402, which providescommunications between computer processor(s) 404, memory 406, persistentstorage 408, communications unit 410, and input/output (I/O)interface(s) 412. Communications fabric 402 can be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system. For example, communications fabric402 can be implemented with one or more buses.

Memory 406 and persistent storage 408 are computer readable storagemedia. In this embodiment, memory 406 includes random access memory(RAM) 414 and cache memory 416. In general, memory 406 can include anysuitable volatile or non-volatile computer readable storage media.

Modeling program 124 and performance program 126 can be stored inpersistent storage 408 for execution and/or access by one or more of therespective computer processors 404 via one or more memories of memory406, as depicted in FIG. 4. In this embodiment, persistent storage 408includes a magnetic hard disk drive. Alternatively, or in addition to amagnetic hard disk drive, persistent storage 408 can include a solidstate hard drive, a semiconductor storage device, a read-only memory(ROM), an erasable programmable read-only memory (EPROM), a flashmemory, or any other computer readable storage media that is capable ofstoring program instructions or digital information.

The media used by persistent storage 408 may also be removable. Forexample, a removable hard drive may be used for persistent storage 408.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage408.

Communications unit 410, in these examples, provides for communicationswith other data processing systems or devices, including clientcomputing device 130 and devices 140A to 140N. In these examples,communications unit 410 includes one or more network interface cards.Communications unit 410 may provide communications through the use ofeither or both physical and wireless communications links. Modelingprogram 124 and performance program 126, shown in FIG. 4, may bedownloaded to persistent storage 408 through communications unit 410.

I/O interface(s) 412 allows for input and output of data with otherdevices that may be connected to server computer 120. For example, I/Ointerface(s) 412 may provide a connection to external device(s) 418 suchas a keyboard, a keypad, a touch screen, and/or some other suitableinput device. External device(s) 418 can also include portable computerreadable storage media such as, for example, thumb drives, portableoptical or magnetic disks, and memory cards. Software and data used topractice embodiments of the present invention, e.g., data managementplatform 122, modeling program 124, performance program 126, and devicedatabase 128, can be stored on such portable computer readable storagemedia and can be loaded onto persistent storage 408 via I/O interface(s)412. I/O interface(s) 412 also connect to a display 420. Display 420provides a mechanism to display data to a user and may be, for example,a computer monitor or an incorporated display screen, such as is used intablet computers and smart phones.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus, theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including anobject-oriented programming language such as Java, Smalltalk, C++ or thelike, and conventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computer,or entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

What is claimed is:
 1. A method for creating a machine-to-machine devicemodel based on ontological relationships, the method comprising:determining, by one or more computer processors, a plurality ofcharacteristics of one or more machine-to-machine devices within amachine-to-machine communication environment; determining, by the one ormore computer processors, one or more ontological relationships betweenthe one or more machine-to-machine devices and the plurality ofcharacteristics of the one or more machine-to-machine devices; andcreating, by the one or more computer processors, a semantic devicemodel, based, at least in part, on the one or more ontologicalrelationships between the one or more machine-to-machine devices and theplurality of characteristics of the one or more machine-to-machinedevices.
 2. The method of claim 1, wherein determining, by the one ormore computer processors, one or more ontological relationships betweenthe one or more machine-to-machine devices and the plurality ofcharacteristics of the one or more machine-to-machine devices furthercomprises: determining, by the one or more computer processors, at leastone ontological relationship between a machine-to-machine device and oneor more performance parameters.
 3. The method of claim 1, whereindetermining, by the one or more computer processors, one or moreontological relationships between the one or more machine-to-machinedevices and the plurality of characteristics of the one or moremachine-to-machine devices further comprises: determining, by the one ormore computer processors, at least one ontological relationship betweena machine-to-machine device and one or more metrological entities. 4.The method of claim 3, further comprising: receiving, by the one or morecomputer processors, a physical quantity measurement from amachine-to-machine device in the machine-to-machine communicationenvironment; and interpreting, by the one or more computer processors,based, at least in part on the determined ontological relationshipbetween the machine-to-machine device and the metrological entity, thephysical quantity measurement.
 5. The method of claim 3, furthercomprising: receiving, by the one or more computer processors, aphysical quantity measurement using a first metrological entity standardfrom a first machine-to-machine device in the machine-to-machinecommunication environment; receiving, by the one or more computerprocessors, a physical quantity measurement using a second metrologicalentity standard from a second machine-to-machine device in themachine-to-machine communication environment; and interpreting, by theone or more computer processors, based, at least in part on thedetermined ontological relationship between the first machine-to-machinedevice and a metrological entity and the determined ontologicalrelationship between the second machine-to-machine device and ametrological entity, the physical quantity measurement received fromeach of the first and the second machine-to-machine devices using,respectively, each of the first metrological entity standard and thesecond metrological entity standard.
 6. The method of claim 1, whereindetermining, by the one or more computer processors, one or moreontological relationships between the one or more machine-to-machinedevices and the plurality of characteristics of the one or moremachine-to-machine devices further comprises: determining, by the one ormore computer processors, at least one ontological relationship betweena machine-to-machine device and one or more business attributes.
 7. Themethod of claim 1, wherein determining, by the one or more computerprocessors, one or more ontological relationships between the one ormore machine-to-machine devices and the plurality of characteristics ofthe one or more machine-to-machine devices further comprises:determining, by the one or more computer processors, at least oneontological relationship between a machine-to-machine device and one ormore hardware components.
 8. The method of claim 1, wherein determining,by the one or more computer processors, one or more ontologicalrelationships between the one or more machine-to-machine devices and theplurality of characteristics of the one or more machine-to-machinedevices further comprises: determining, by the one or more computerprocessors, at least one ontological relationship between amachine-to-machine device and one or more software components.
 9. Themethod of claim 1, wherein determining, by the one or more computerprocessors, one or more ontological relationships between the one ormore machine-to-machine devices and the plurality of characteristics ofthe one or more machine-to-machine devices further comprises:determining, by the one or more computer processors, at least oneontological relationship between a machine-to-machine device and one ormore protocols.
 10. The method of claim 1, wherein determining, by theone or more computer processors, one or more ontological relationshipsbetween the one or more machine-to-machine devices and the plurality ofcharacteristics of the one or more machine-to-machine devices furthercomprises: determining, by the one or more computer processors, at leastone ontological relationship between a machine-to-machine device and oneor more connectivity mediums.
 11. The method of claim 1, whereindetermining, by the one or more computer processors, one or moreontological relationships between the one or more machine-to-machinedevices and the plurality of characteristics of the one or moremachine-to-machine devices further comprises: determining, by the one ormore computer processors, at least one ontological relationship betweena machine-to-machine device and one or more device attributes.